Elements of information theory

Following a brief introduction and overview, early chapters cover the basic algebraic relationships of entropy, relative entropy and mutual information, AEP, entropy rates of stochastics processes and data compression, duality of data compression and the growth rate of wealth. Later chapters explore Kolmogorov complexity, channel capacity, differential entropy, the capacity of the fundamental Gaussian channel, the relationship between information theory and statistics, rate distortion and network information theories. The final two chapters examine the stock market and inequalities in information theory. In many cases the authors actually describe the properties of the solutions before the presented problems.

À propos de l'auteur (1991)

About the authors THOMAS M. COVER is Professor jointly in the Departments of Electrical Engineering and Statistics at Stanford University. He is past President of the IEEE Information Theory Society and is a Fellow of the Institute for Mathematical Statistics and of the IEEE. In 1972 he received the Outstanding Paper Award in information Theory for his paper "Broadcast Channels," and he was selected in 1990 as the Shannon Lecturer, regarded as the highest honor in information theory. Author of over 90 technical papers, he is coeditor of the book Open Problems in Communication and Computation. Professor Cover has devoted the last 20 years to developing the relationship between information theory and statistics. He received his PhD in electrical engineering from Stanford University. JOY A. THOMAS is working at the IBM T. J. Watson Research Center in Hawthorne, New York. He received the IEEE Charles LeGeyt Fortescue Fellowship for 1984–85 and the IBM Graduate Fellowship for 1987–90. He received his BTech in electrical engineering at the Indian Institute of Technology Madras, India and his PhD in electrical engineering at Stanford University.